Nationalism in the Age of Brexit: The Attitudes and Identities of Young Voters
Bibliographic record
Abstract
The 2016 Brexit referendum revealed a division between younger voters, a majority of whom voted Remain, and older voters, a majority of whom voted Leave. From virtual interviews with six British young adults, this article analyzes the effects of the Brexit referendum on their perceptions of belonging and national identity. My theoretical framework draws upon Benedict Anderson’s definition of the nation and Michael Skey’s and Craig Calhoun’s critique that feelings of equality among members are unrealistic due to the power and identity hierarchies that exist within a nation. Interviews reveal a strong binary conception of identities created through politics and media that divide voters into distinct, distanced groups. Young voters use harsh, derogatory language to describe oppositional groups, such as Conservatives, Leave voters, and older voters, to separate themselves and reinforce their identities. However, because these oppositional groups hold the most power, continuous separation reinforces feelings of powerlessness in politics and reveals hierarchies of identities. These hierarchies can have long-lasting implications for the United Kingdom as these younger voters will eventually comprise the voting majority and strive to see their values and beliefs represented in positions of power.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".